Data operations manager állás, munka

• You plan, coordinate, and monitor initiatives under the KM 2.0 strategy.
• You maintain project plans, milestones, and status reports, and track progress, risks, and dependencies.
• You support prioritization, resource allocation, and risk management across different workstreams.

Lead the design, development, and evolution of suena's backend and API infrastructure—ensuring scalability, performance, and reliability as our platform grows....

Design and develop scalable data architectures for integrating our tailored and standard software solutions into our clients' environments, collaborating with professional services, software engineering and cloud operations....

Develop and maintain data architecture: create and manage robust data architectures that support high-volume, high-throughput SaaS applications, focusing on reliability and scalability....

• Design, develop, and implement platform solutions that enhance the reliability, security, and scalability of the AI Platform infrastructure.
• Provide technical leadership in cloud infrastructure, networking, CI/CD, and security for AI and MLOps workloads.

You build, validate, and analyse finite element models (FEA/FEM) for structural, crash, noise, vibration, roughness, and aerodynamic simulations....

• You own the strategy and roadmap for domain specific foundation models; align with engineering and production leaders.
• You build and adapt large language, reasoning, and multimodal models for automation at scale.

• Drive business development efforts focused on Technology Transformation and Data & AI solutions within the local market.
• Build and maintain strong relationships with local financial institutions, including banks and wealth and asset managers.

• You will take overall technical responsibility for complex, cross-functional AI initiatives - from requirements analysis through to implementation.
• You will independently identify, evaluate and manage AI-related projects.

Design and deliver AI-driven solutions for Swiss Financial Services clients, focusing on Agentic AI, intelligent automation, AI enablement, data engineering, and scalable application development....

• Define and prioritize product features and roadmap aligned with business goals
• Own the product backlog and ensure clarity and feasibility as well as maintaining of user stories , epics and features
• Collaborate with SCRUM/Nexus teams to drive agile development cycles

implement and productionise ML-based services on our AI- and big-data-platform Databricks, using Python, SQL and Linux....

• Evaluate customer needs and define & justify new solutions and improvements co-developed in HW and SW
• Collaborate in interdisciplinary projects from the business plan to the product release

• Partner with stakeholders to identify, design and evaluate AI solutions by translating complex business challenges into practical ML and GenAI use cases
• Lead data-driven projects, from requirements analysis to implementation, with a strong focus on business impact

• Design and lead development of AI products for business-specific use cases.
• Mentor and guide the software engineering team, setting clear technical directions and providing architectural oversight.

• You support the development and implementation of BI solutions.
• You conduct data analyses to identify trends.
• By presenting complex data clearly and understandably, you assist us in creating reports.
• You assist in designing and optimizing data architectures.

• Work closely with product owners and stakeholders to analyze business needs and integrate them into the CRM system
• Define and enforce CRM development standards based on best practices and governance models
• Configure the system, workflows, automation, and integrate it with third-party systems

• Deliver creative customer facing features to bring German users on chain.
• Articulate a long term vision for maintaining and scaling our backend systems.

System Architecture Specifications: Create and maintain architecture specifications, interface definitions, and integration plans as the foundation for hardware, firmware, and software development teams....

• Design, configure, and optimize interactions with LLMs through retrieval-augmented generation (RAG), and orchestration.
• Implement tool-calling patterns to integrate LLMs with SaaS tools and APIs.
• Leverage fine-tuning or parameter-efficient techniques for performance enhancement.